EET&D   : Rodger, I think we can probably agree that we begin our discussion today at a very pivotal point in the evolution of the utilities industry. Many utilities have rolled out, or are rolling out, widespread technology initiatives that generate—via smart meters and other systems—a wealth of data. Do you think utilities are actually prepared to manage and make use of the massive data volumes they are collecting?

  Smith   : Today, as a result of smart meters and other systems, utilities are forced to deal with unprecedented amounts of interval, voltage, and interruption information. Simultaneously, a new generation of grid nodes and sensors detects and reports every system anomaly while adding to utilities’ already overburdened asset inventory. Meanwhile, production systems churn out reams of new financial, customer, and staffing information. Utilities have not previously had access to much of this information.

I think the main questions we need to ask include, “How will access to this new data change the way utilities drive their businesses?” and “Will predictive analytics spur operational change?”

In fact, along those lines, Oracle recently surveyed more than 150 executives at North American utilities with smart meter programs in place to gauge their perceptions on the business impact of “big data,” their preparedness to handle this huge data growth, and their plans to extract optimal business value from this data to better target, engage with, and serve their customers.

We found that the average utility with at least one smart meter program in place has increased the frequency of its data collection by 180x—collecting data once every four hours as opposed to just once a month. While that might not be very surprising, it’s still a big number. The good news is that utilities with smart meter programs in place say they are somewhat prepared to manage the data deluge, rating themselves a 6.7 on a scale of 1 to 10. Utilities also said that they are collecting critical information, such as outage (78%) and voltage data (73%), and many are using it to support business operations, improve service reliability, and enhance customer satisfaction.

However, there is still significant opportunity on the horizon.

  EET&D   : Could you expand on your last point a bit?

  Smith   : Utilities can use the massive data volumes they collect from smart meters and other systems to place a renewed focus on network and service reliability.

Unprecedented data availability—coupled with sophisticated analytics solutions—will drive utilities to evolve many aspects of their businesses. For example, asset risk analysis will help utilities to identify and avoid operational risks, such as major/catastrophic events. Utilities can integrate work and asset management systems with field operational performance data to better assess risk.
Another change-enabler I see is utilities’ growing use of distributed intelligence for distributed generation management and distribution automation. Utilities can further improve reliability through automated self-restoring and system optimization controls to ultimately improve customer satisfaction.

I believe we will also see an increased use of mobile workforce management and asset management systems to support knowledge transfer between aging field workforce and “digital native” new hires. Mobile workforce management systems will pay for themselves based on crew efficiency, but utilities will derive the real value from field information management and data quality gains.
I could go on and on and on, but I think I covered some of the more important points here.

  EET&D   : So, it’s not just about smart meters, is it?

  Smith   : Smart meters are certainly bringing in a constant stream of outage, interval, and voltage information—but they’re not the only sources contributing to utilities’ data overflow. Other sources include outage/distribution management, customer data/feedback, alternative energy sources, as well as advanced sensors, controls, and grid-healing elements.

The majority of our survey respondents said that drawing intelligence from smart grid/smart meter data is among their top three priorities, however, the average utility is just somewhat prepared to handle the data deluge—noting deficiencies in analytics. Our study found that today, even though utilities have access to unprecedented volume and variety of data from smart grid roll-outs, 45% of them struggle to report information to business managers as fast as they need it and 50% miss opportunities to deliver useful information to their customers. The study also found that utilities see a need to improve their ability to translate information into actionable intelligence and leverage data for strategic decision-making. We also asked respondents if they had a meter data management (MDM) system in place, and found that 70% of those with an MDM system said they are prepared to successfully manage the data influx versus just 51% of those without.

It’s not about just collecting data—utilities must have the right systems, people, and processes in place to analyze the data, report on it, and act on it—to improve business operational efficiency, service reliability, and customer engagement. Otherwise, it will be impossible to make sense of the staggering amount of data they’re collecting from smart meters and other smart grid components.

  EET&D   : How can utilities specifically use the data they’re collecting and what types of analysis should they perform?

  Smith   : As utilities gain the ability to analyze big data, they will realize deeper levels of insight into how their own businesses operate and into their customers’ needs.

Efficient transmission and distribution (T&D) infrastructure management has always been a top priority for utilities, and it remains a key component of any smart grid strategy. With the influx of new T&D smart grid data, asset management complexity has grown as well.

Today—through work and asset management systems, geographic information systems, supervisory control and data acquisition (SCADA) systems, sensors, grid nodes, mobile devices, and more— utilities have real-time visibility into the conditions and performance of specific assets, opening up a whole new world of possibilities for optimizing asset management. Work and asset management systems integrate to field operational performance data to enable utilities to identify potential issues and better assess risk. Moreover, analytics capabilities provide insights that help utilities determine the best time to repair or replace assets—helping them to reduce maintenance costs and make the right buying decisions.

Further, utilities can use the “big data” they’re collecting from their customers—from website communications, social media engagement, etc.—to provide better, more personalized services based on customer needs.

With integrated systems and the sophisticated analytics tools available today, utilities can move toward developing a true 360-degree view of every aspect of their businesses—helping them transform processes and support effective decision-making.

  EET&D   : What types of tools and skill-sets should utilities evaluate to enable this level of analysis?

  Smith   : As data management becomes more and more complex, utilities need open, standards-based IT systems that allow for easy integration and data sharing. They need access to business intelligence tools that are tailored to their specific needs. These tools for statistical and advanced analysis must work with distributed data to perform analysis regardless of where the data resides, scale as data volume grows, and automate decisions based on analytical models. Underneath it all, utilities need the foundational database, hardware, and storage for superior reliability, performance, and security. All of these solutions should be modular and flexible – providing utilities with choices, enabling them to implement what they need, when they need it, to address the challenges that are most important to them.

But they also need the right people to do the job. There is a unique skill-set required to examine patterns in unstructured data. Investment in people is very important.

  EET&D   : Are you seeing any other factors emerge that weren’t originally included in utilities’ business cases for smart meters?

  Smith   : Today, we’re seeing a growing focus on load forecasting and asset management.

The initial smart grid value proposition was around providing better information to customers to drive smarter energy use, as well as supporting demand response and conservation programs. Those are, of course, still important. But, we are seeing an increased focus on leveraging the data generated by smart grids to improve network performance, distribution management, and asset optimization. These improvements will lead to more satisfied customers while they drive process improvements and cost reductions for utilities. Intelligent load forecasting, for example, enables utilities to identify how much electricity they will need in the future, predict monthly sales revenue and unbilled consumption, and support asset management, load analysis, and predictive maintenance.

If utilities can generate more accurate load profiles, they can better anticipate their forecasted load. If they can dial back their traditional overage calculation by even a couple percent, they can potentially save millions of dollars. In addition, they can look at excess system load and sell that back into the grid—another huge cost savings.

  EET&D   : To close, what other trends are on the horizon in the short term?

  Smith   : With data coming in from every corner of the business— from outage/distribution management, alternative energy sources, advanced sensors, controls, grid-healing elements, etc.—utilities have the opportunity to use that data to improve operational performance across every aspect of their businesses—from asset reliability and replacement planning, to load forecasting and distribution management, to customer communications and conservation programs.

As our survey results indicated, utilities must not only make data collection a priority, but invest in the systems and people needed to make sense of a growing number of new data sources collected from smart meters and other smart grid components. In addition to streamlining business operations, successful data management should greatly improve the customer experience—both through improved outage management/service reliability and stronger customer communication around smart grid changes and benefits.

I truly look forward to what the future holds for the utilities industry. I’m excited to be a part of it, and think we’re on the brink of something really great.

  EET&D   : We want to thank you Rodger for taking the time out of a busy schedule to share your knowledge, experience, and insights with our readers. We agree with you that the utilities industry is headed for some very exciting times particularly in the realm of data management.


Rodger E. Smith is senior vice president and general manager for the Oracle Tax and Utilities Global Business Unit. In this position, he leads the global business unit’s solution groups, strategic planning, product development, sales, service, and support.

Mr. Smith is the former president of Enterprise Management Solutions (EMS), the management consulting division of Black & Veatch. In this position, he grew the division into one of the largest management consulting organizations specializing in energy and water. He previously held positions with PricewaterhouseCoopers and Southern Company, one of the largest electric utilities in the United States.